Advanced Control Architectures for Intelligent MicroGrids, Part I:Decentralized and Hierarchical Control

This paper presents a review of advanced control techniques for microgrids. This paper covers decentralized, distributed, and hierarchical control of grid-connected and islanded microgrids. At first, decentralized control techniques for microgrids are reviewed. Then, the recent developments in the stability analysis of decentralized controlled microgrids are discussed. Finally, hierarchical control for microgrids that mimic the behavior of the mains grid is reviewed

Dynamic Time-Lag Regression: Predicting what & when

This paper tackles a new regression problem, called Dynamic Time-Lag Regression (DTLR), where a cause signal drives an effect signal with an unknown time delay. The motivating application, pertaining to space weather modelling, aims to predict the near-Earth solar wind speed based on estimates of the Sun’s coronal magnetic field. DTLR differs from mainstream regression and from sequence-to-sequence learning in two respects: firstly, no ground truth (e.g., pairs of associated sub-sequences) is available; secondly, the cause signal contains much information irrelevant to the effect signal (the solar magnetic field governs the solar wind propagation in the heliosphere, of which the Earth’s magnetosphere is but a minuscule region).A Bayesian approach is presented to tackle the specifics of the DTLR problem,with theoretical justifications based on linear stability analysis. A proof of concept on synthetic problems is presented. Finally, the empirical results on the solar wind modelling task improve on the state of the art in solar wind forecasting

Using gradient boosting regression to improve ambient solar wind model predictions

Studying the ambient solar wind, a continuous pressure‐driven plasma flow emanating from our Sun, is an important component of space weather research. The ambient solar wind flows in interplanetary space determine how solar storms evolve through the heliosphere before reaching Earth, and especially during solar minimum are themselves a driver of activity in the Earth’s magnetic field. Accurately forecasting the ambient solar wind flow is therefore imperative to space weather awareness. Here we present a machine learning approach in which solutions from magnetic models of the solar corona are used to output the solar wind conditions near the Earth. The results are compared to observations and existing models in a comprehensive validation analysis, and the new model outperforms existing models in almost all measures. In addition, this approach offers a new perspective to discuss the role of different input data to ambient solar wind modeling, and what this tells us about the underlying physical processes. The final model discussed here represents an extremely fast, well‐validated and open‐source approach to the forecasting of ambient solar wind at Earth

Electrical load emulation using optimal feedback control technique

The paper presents a method of emulating electrical loads using power electronic converters. The loads include machines such as induction motors and their associated mechanical load and also more complex machine systems such as wind-driven generators. The load emulator is effectively a dynamically controllable source or sink which is capable of bidirectional power exchange with either a grid or another power electronic converter system. Using load emulation, the feasibility of connecting a particular machine to a grid under various load conditions can be examined without the need for any electromechanical machinery. The paper considers the case of a power electronic Voltage Source Inverter (VSI) emulating a three phase induction motor connected to a three phase ac grid. The VSI is operated in a mode where the current drawn from the ac grid is controlled by closed loop control. Experimental results are provided to verify the scheme

Design and analysis of stand-alone 4-wire, 4-leg inverter microgrid with unbalanced loads

Three phase 3-leg inverters are the most common interfaces for forming distributed generation and microgrids. However, in low voltage systems, loads are often 3-phase, 4-wire with frequent unbalances. The question of unbalanced loads on stand-alone microgrids can be handled in two ways. First, unbalanced load compensators can be provided near each unbalanced load. Second, unbalanced loads can be fed by 4-leg inverter interfaces with a 4-wire microgrid. This paper is concernedwith the second approach. The design of closed-loop system for 4-leg inverter interface for microgrid with unbalanced loads is carried out. Detailed analysis of power flow dynamics and stability for a 3-phase, 4-wire microgrid with 4-leg inverters catering to unbalanced loads is reported. The analysis is supported by simulations and laboratory experiments. The proposed microgrid shows stable operation andmaintains balanced voltages at unbalanced load terminals without any load compensators

Electrical load emulation using power electronic converters

The paper presents a method of emulating electrical loads using power electronic converters. The loads include machines such as induction motors and its associated mechanical load and also more complex machine systems such as wind power generation systems. The load emulator is effectively a dynamically controllable source or sink which is capable of bidirectional power exchange with either a grid or another power electronic converter system. Using load emulation, the feasibility of connecting a particular load to a grid under various conditions can be studied in the absence of any electromechanical machinery. This paper considers the case of a power electronic Voltage Source Inverter (VSI) emulating a three phase induction motor connected to a three phase ac grid. The VSI is operated in a mode where the current drawn from the ac grid is controlled by closed loop control. Experimental results have been provided to verify the scheme